SynthesisF1000Research2021
Data extraction methods for systematic review (semi)automation: Update of a living systematic review.
Synthesis in F1000Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- A systematic review and evaluation framework for IoB-based adaptive health coaching systems.Frontiers in digital health · 2026Pooled it
- Wild birds as environmental reservoirs of antimicrobial-resistantFrontiers in microbiology · 2026Pooled it
- Exploring the psychological well-being of midwives after maternal deaths: an integrative review.Frontiers in psychology · 2026Pooled it
- Effectiveness of self-management interventions on Type 2 diabetes among young adults (18-45 years): A systematic review and meta-analysis.Diabetic medicine : a journal of the British Diabetic Association · 2025Pooled it
- Unlocking the Hidden Value of Evaluation Reports: A Semi-Automated Workflow to Inform Strategic Planning and Monitoring of SDG Progress Within UNICEF.Campbell systematic reviews · 2026Article
- Artificial Intelligence (AI) Readiness to Support Evidence Synthesis by Workflow: Findings From a Review of Reviews.Campbell systematic reviews · 2026Article
- Mental health impacts of climate change on vulnerable populations in Nigeria and Japan: A systematic review of access to emergency healthcare.Public health in practice (Oxford, England) · 2026Review
- Genomic newborn screening: a scoping review of the field's evolution and associated ethical, legal, and social implications.European journal of human genetics : EJHG · 2026Article
- Topic-specific living databases of clinical trials: A scoping review of public databases.Clinical trials (London, England) · 2026Article
- Study protocol for evaluating automation of systematic review processes with EPPI-Reviewer and Copilot 365 in updating the cataract evidence gap map.Systematic reviews · 2026Article
- The landscape of artificial intelligence tools and platforms for evidence synthesis: a scoping review.Systematic reviews · 2026Article
- The Phases of Living Evidence Synthesis Using AI AI: Living Evidence Synthesis (Version 1).Journal of medical Internet research · 2026Article
- Automating the data extraction process for systematic reviews using GPT-4o and o3.Research synthesis methods · 2026Article
- Artificial Intelligence-Assisted Data Extraction With a Large Language Model: A Study Within Reviews.Annals of internal medicine · 2025Article
- Assessing Data Quality in Heterogeneous Health Care Integration: Simulation Study of the AIDAVA Framework.JMIR medical informatics · 2025Article
- Applying machine learning to enhance core outcome set development: automating the data extraction and classification of outcomes.Journal of orthopaedic surgery and research · 2025Article
- A step-by-step guide for conducting an umbrella review.Tropical medicine and health · 2025Review
- Article
- Artificial Intelligence and Automation in Evidence Synthesis: An Investigation of Methods Employed in Cochrane, Campbell Collaboration, and Environmental Evidence Reviews.Cochrane evidence synthesis and methods · 2025Article
- Accelerating clinical evidence synthesis with large language models.NPJ digital medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Background: The reliable and usable (semi) automation of data extraction can support the field of systematic review by reducing the workload required to gather information about the conduct and results of the included studies. This living systematic review examines published approaches for data extraction from reports of clinical studies. Methods: We systematically and continually search PubMed, ACL Anthology, arXiv, OpenAlex via EPPI-Reviewer, and the Results: 117 publications are included in this review. Of these, 30 (26%) used full texts while the rest used titles and abstracts. A total of 112 (96%) publications developed classifiers for randomised controlled trials. Over 30 entities were extracted, with PICOs (population, intervention, comparator, outcome) being the most frequently extracted. Data are available from 53 (45%), and code from 49 (42%) publications. Nine (8%) implemented publicly available tools. Conclusions: This living systematic review presents an overview of (semi)automated data-extraction literature of interest to different types of literature review. We identified a broad evidence base of publications describing data extraction for interventional reviews and a small number of publications extracting other study types. Between review updates, large language models emerged as a new tool for data extraction. While facilitating access to automated extraction, they showed a trend of decreasing quality of results reporting, especially quantitative results such as recall and lower reproducibility of results. Compared with the previous update, trends such as transition to relation extraction and sharing of code and datasets stayed similar.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.